Data analysis forms part of the three core elements of any good research paper- Research questions, experimental design and data analysis. If you want to publish good work, these three need to be in place and on target.

As a scientist, the first two may come naturally, but if you are anything like me – then data analysis is not your strong point. Sure, you can always pay someone to do it for you, but you will still have to interpret the results and write it up. For this reason, it is best if you at least understand what needs to be done, and what the results mean, before you attempt to do analysis yourself or hire someone to do it for you.

So here is a short introduction to data analysis, why you need it and how to start.

Why analyze data?

The answer is short and simple – data analysis is needed because without it, your data would only be numbers and figures without any meaning. By definition, “data analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense, recap and evaluate data” (Source).

In layman’s terms, data analysis attempts to separate the noise from the message in your data, so you can draw the right conclusions. Most people think of data analysis as statistical analysis, and although it includes statistical procedures, it is not exclusively restricted to only that. In fact, data analysis in most instances is a continuous process of pattern recognition and observation that starts with project planning and only ends when the project is completed.

Data analysis also ensure scientific integrity, as the techniques of data analysis are standardized across many platforms and research fields, thus acting as a form of quality control.

Data analysis – the process

Data analysis starts along with project planning and follows the 5 steps listed below:

  1. Decide on data analysis methods

This is an important and first step in data analysis. If you are not qualified or are planning to become qualified in data analysis during the project, it may be a very feasible option for you to enlist professional help. Data analysts should be incorporated early on in the project planning phase, to ensure that the correct data is collected and the appropriate analysis are conducted.

During the planning phase, you will decide on the best method of data analysis, which includes statistical analysis. This will ideally be incorporated into your project proposal that will be sent to finders and supervisors and will help determine the feasibility of the whole project. If you are planning on performing the analysis yourself, at this stage you should also plan to acquire the correct software and skill to be able to perform the data collection and analysis.

  1. Select the best data collection methods

How you collect your data is dependent on the statistical analysis you will be performing. Make sure that you collect all the necessary data you will need to be able to accurately perform your analysis, as going back and re-running experiments are usually impossible – especially when it comes to sensitive data.

  1. Collect the data and analyze

Now data collection can begin, and as you go you will be able to make some preliminary observations and inferences. Take note of these as they will be able to either confirm your statistical findings in many cases.

Once the data has been collected, the actual statistical analysis can begin, either with the use of a professional analyst or through the use of specific software.

  1. Draw an unbiased inferences

From the analysis results, you will be able to draw certain inferences based on the trends and patterns identified by the analyst or software. Make sure you are aware of how to accurately report these findings.

Now, use this data and place it into context in terms of other studies and findings. You should be able to come up with direct answers to your research questions at this point – and these should be answered in the discussion section of your research paper.

  1. Data presentation & Write up

Finally, decide on the clearest and shortest way of presenting your data. These could include tables, graphs, figures or statistical results written up in the text. Based on these, finalize your write up.

Final Words:

Whether you do the data analysis yourself or hire someone to do it for you, it very important to have some basic idea about the process. It will save you time as well as money.

Hire the professionals who can also provide you with a technical editing of your work. This will make sure that your work is thoroughly revised of any errors and is publication ready. Consider Advaita services for such support.